Tire non-uniformity relates to the symmetry (or lack of symmetry) relative to the tire's axis of rotation in certain quantifiable characteristics of a tire. Conventional tire building methods unfortunately have many opportunities for producing non-uniformities in tires. During rotation of the tires, non-uniformities present in the tire structure produce periodically-varying forces at the wheel axis. Tire non-uniformities are important when these force variations are transmitted as noticeable vibrations to the vehicle and vehicle occupants. These forces are transmitted through the suspension of the vehicle and may be felt in the seats and steering wheel of the vehicle or transmitted as noise in the passenger compartment. The amount of vibration transmitted to the vehicle occupants has been categorized as the “ride comfort” or “comfort” of the tires.
Tire uniformity parameters, or attributes, are generally categorized as dimensional or geometric variations (radial run out and lateral run out), mass variance, and rolling force variations (radial force variation, lateral force variation and tangential force variation, sometimes also called longitudinal or fore and aft force variation). Uniformity measurement machines often calculate the above and other uniformity characteristics by measuring force at a number of points around a tire as the tire is rotated about its axis to generate a uniformity waveform.
A measured uniformity waveform for a tire can result from manufacturing effects that have both tire effects and process effects. Examples of tire effects include effects due to tire material components (e.g., the product start point or joint overlap location of one or more of casing textile plies, belt plies, bead rings, inner liner, tread and other rubber layers of the tires), manufacturing techniques (e.g., the relative location in which a green tire is introduced on a building drum, placed into a mold or curing press, and the like), and/or controllable conditions used in the tire construction process (e.g., the temperature and pressure at which green tires are subjected during the curing process or other manufacturing steps.) Examples of process effects may arise from such manufacturing conditions as a roller influence, extruder surge, fluctuation in a process condition (e.g., temperature, pressure, speed, etc.) and others.
The impact of tire effects and process effects within a measured uniformity waveform are respectively represented by “tire harmonic” or “process harmonic” components of the composite uniformity waveform. A tire harmonic component has a period that fits an integer number of times within the tire circumference. A process harmonic component has a period that does not fit an integer number of times within the tire circumference.
An example known technique for estimating the magnitude of process harmonic components (i.e. process harmonic magnitudes) involves estimating process harmonic magnitudes for one or more candidate process effects for each tire using a regression analysis. The process harmonic magnitudes for each tire are then averaged to provide an estimate of the process harmonic magnitudes associated with each candidate process effect. There can be practical limits for this technique based on the discrimination of different process harmonics when multiple process effects are identified as candidates for analysis, particularly when the rates of introduction of the candidate process effects are close together. These limits can result at least in part from the sampling resolution of uniformity measurements (e.g. 128 points for each tire) performed for each tire. In particular, it can be difficult to separate candidate process effects having rates of introduction that are spaced more closely than the sampling resolution of the measurement points on the tire allow.
In addition, a process harmonic will typically have a peak (e.g. a maximum magnitude) located at different points in different tires. In other words, the peak of the process harmonic will shift from tire to tire. This can result in the peak of the process effect being located between two discrete measurement points on the tire as opposed to exactly co-located with any observed measurement point. The measurement points do not naturally sample the same points of the process effect when multiple tires are considered.
Thus, a need exists for improving the sampling resolution of uniformity data for estimation of process harmonic magnitudes. A system and method that can increase the sampling resolution of the uniformity data without requiring stacking of tires would be particularly useful.